@ARTICLE {McIntireFajardo2009,
AUTHOR = {McIntire, E.J.B. and Fajardo, A.},
TITLE = {Beyond description: the active and effective way to infer processes
from spatial patterns},
JOURNAL = {Ecology},
YEAR = {2009},
VOLUME = {90},
PAGES = {46-56},
NUMBER = {1},
URL = {http://www.esajournals.org/doi/pdf/10.1890/07-2096.1},
MONTH = {jan},
AF = {McIntire, Eliot J. B. and Fajardo, A.},
DE = {a priori inference; competition; dispersal; diversity; ecologicalEOLEOLprocesses;
invasion; space as a surrogate; spatial pattern; spatialEOLEOLresiduals},
PG = {11},
SN = {0012-9658},
UT = {ISI:000263318700008},
ABSTRACT = {The ecological processes that create spatial patterns have been examined
by direct measurement and through measurement of patterns resulting
from experimental manipulations. But in many situations, creating
experiments and direct measurement of spatial processes can be difficult
or impossible. Here, we identify and de. ne a rapidly emerging alternative
approach, which we formalize as "space as a surrogate'' for unmeasured
processes, that is used to maximize inference about ecological processes
through the analysis of spatial patterns or spatial residuals alone.
This approach requires three elements to be successful: a priori
hypotheses, ecological theory and/or knowledge, and precise spatial
analysis. We offer new insights into a long-standing debate about
process-pattern links in ecology and highlight six recent studies
that have successfully examined spatial patterns to understand a
diverse array of processes: competition in forest-stand dynamics,
dispersal of freshwater fish, movement of American marten, invasion
mechanisms of exotic trees, dynamics of natural disturbances, and
tropical-plant diversity. Key benefits of using space as a surrogate
can be found where experimental manipulation or direct measurements
are difficult or expensive to obtain or not possible. We note that,
even where experiments can be performed, this procedure may aid in
measuring the in situ importance of the processes uncovered through
experiments.},
KEYWORDS = {PLANT-COMMUNITIES; STATISTICAL-ANALYSIS; MULTIPLE SCALES; ECOLOGICAL
DATA; PATH-ANALYSIS; COMPETITION; DYNAMICS; MODELS; TREE; POPULATIONS},
OWNER = {brugerolles},
TIMESTAMP = {2009.02.26},
}